{"id":"W3174717610","doi":"10.1007/978-3-030-80599-9_28","title":"Using Document Embeddings for Background Linking of News Articles","year":2021,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Topic Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Embedding; Pooling; Information retrieval; Variety (cybernetics); Security token; Natural language processing; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001553363,0.002258795,0.001071631,0.006961254,0.00088597,0.002929856,0.001071436,0.001728956,0.007684884],"category_scores_gemma":[0.006627091,0.0006969051,0.001254675,0.004879933,0.0002822509,0.005069684,0.002071514,0.002061447,0.009282964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005967126,"about_ca_system_score_gemma":0.0007412162,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003042084,"about_ca_topic_score_gemma":0.004965898,"domain_scores_codex":[0.9988802,0.0002622278,0.00009667877,0.0004386534,0.0001922441,0.000130001],"domain_scores_gemma":[0.9963003,0.00189939,0.0002672757,0.0005496152,0.0007571648,0.000226417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009823543,0.0006412656,0.004914255,0.0005483353,0.0002632014,0.0003103518,0.0003602342,0.01061495,0.014907,0.003984306,0.05532736,0.9071463],"study_design_scores_gemma":[0.000167739,0.0004401254,0.00758181,0.0002955194,0.0006783026,0.0006499334,0.0007057262,0.8815923,0.0290948,0.02588786,0.05278309,0.0001228059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1257327,0.01018448,0.7878379,0.001389093,0.004065636,0.0004794594,0.01304538,0.03602471,0.02124062],"genre_scores_gemma":[0.4582685,0.004802422,0.4464044,0.0004246914,0.002735849,0.0003726273,0.05390292,0.003520703,0.02956784],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007684884,"threshold_uncertainty_score":0.0257085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06072423983579282,"score_gpt":0.3040035160247984,"score_spread":0.2432792761890056,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}